Bivariate quantitative trait linkage analysis: Pleiotropy versus co- incident linkages

Laura Almasy, Thomas D. Dyer, John Blangero

    Research output: Contribution to journalArticlepeer-review

    290 Scopus citations


    Power to detect linkage and localization of a major gene were compared in univariate and bivariate variance components linkage analysis of three related quantitative traits in general pedigrees. Although both methods demonstrated adequate power to detect loci of moderate effect, bivariate analysis improved both power and localization for correlated quantitative traits mapping to the same chromosomal region, regardless of whether co- localization was the result of pleiotropy. Additionally, a test of pleiotropy versus co-incident linkage was shown to have adequate power and a low error rate.

    Original languageEnglish (US)
    Pages (from-to)953-958
    Number of pages6
    JournalGenetic epidemiology
    Issue number6
    StatePublished - 1997


    • Linkage analysis
    • Pleiotropy
    • Quantitative traits
    • Statistical genetics

    ASJC Scopus subject areas

    • Epidemiology
    • Genetics(clinical)


    Dive into the research topics of 'Bivariate quantitative trait linkage analysis: Pleiotropy versus co- incident linkages'. Together they form a unique fingerprint.

    Cite this